Understand how implementing different data structures and algorithms intelligently can make your Python code and applications more maintainable and efficient Key Features • Explore functional and reactive implementations of traditional and advanced data structures • Apply a diverse range of algorithms in your Python code • Implement the skills you have learned to maximize the performance of your applications Book Description Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You'll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer. By the end of this Python book, you'll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications. What you will learn • Understand common data structures and algorithms using examples, diagrams, and exercises • Explore how more complex structures, such as priority queues and heaps, can benefit your code • Implement searching, sorting, and selection algorithms on number and string sequences • Become confident with key string-matching algorithms • Understand algorithmic paradigms and apply dynamic programming techniques • Use asymptotic notation to analyze algorithm performance with regard to time and space complexities • Write powerful, robust code using the latest features of Python Who this book is for This book is for developers and programmers who are interested in learning about data structures and algorithms in Python to write complex, flexible programs. Basic Python programming knowledge is expected.
The objective of this monograph is to improve the performance of the sentiment analysis model by incorporating the semantic, syntactic and common-sense knowledge. This book proposes a novel semantic concept extraction approach that uses dependency relations between words to extract the features from the text. Proposed approach combines the semantic and common-sense knowledge for the better understanding of the text. In addition, the book aims to extract prominent features from the unstructured text by eliminating the noisy, irrelevant and redundant features. Readers will also discover a proposed method for efficient dimensionality reduction to alleviate the data sparseness problem being faced by machine learning model. Authors pay attention to the four main findings of the book : -Performance of the sentiment analysis can be improved by reducing the redundancy among the features. Experimental results show that minimum Redundancy Maximum Relevance (mRMR) feature selection technique improves the performance of the sentiment analysis by eliminating the redundant features. - Boolean Multinomial Naive Bayes (BMNB) machine learning algorithm with mRMR feature selection technique performs better than Support Vector Machine (SVM) classifier for sentiment analysis. - The problem of data sparseness is alleviated by semantic clustering of features, which in turn improves the performance of the sentiment analysis. - Semantic relations among the words in the text have useful cues for sentiment analysis. Common-sense knowledge in form of ConceptNet ontology acquires knowledge, which provides a better understanding of the text that improves the performance of the sentiment analysis.
About the Book: A species has a unique instinctive and singular behavioural pattern. All creatures belonging to a species have similar traits and their response to a stimulus is predictable. Not so in the case of human beings. From the stage of the Neanderthals, mankind has evolved in a distinctive manner, in overwhelming divisions — religious, political, regional, national, language, dress, education, etc. The list is long. Every identity has unique characteristics and rituals imposed on its members. Every creature is a different animal; the only thing common is the anatomy. This kaleidoscope of mortals, collectively called humans, is brutally cruel yet spiritually empathetic; kills fellow beings for trivialities yet gives its life for ephemeral emotions; embraces the strangers yet shuns one's kin; eulogises simplicity yet yearns for wealth — a world of striking contradictions. Every human conducts itself as per its taming, wearing a socially acceptable mask. But even a simple provocation dissolves the mask, and it comes to its natural self. The author has narrated situations arising from the conflict between the real self and the socially conditioned being in the stories in this collection. About the Author: Basant Kumar holds a degree in Science from the University of Allahabad. He graduated in Civil Engineering with Honours from the University of Roorkee (now IIT Roorkee). He was awarded the University Silver Medal. He retired as the Additional Secretary, Government of India. Very active post-retirement, as an independent freelance consultant in the field of Civil Engineering, he is also an Arbitrator and an Arbitration Consultant. He experienced various facets of life in several fields of activities and multifarious pursuits, as an engineer, administrator, and manager in the corporate world and also on the sports field. This vast exposure left a deep and indelible imprint of the human conduct in different situations on him. He intimately observed the compulsions, fears, and ambitions that navigated people on the path that they traversed in life. The stories in this collection bring out the subtleties of choices that protagonists make driven by their inner fragilities and fortitude. Basant Kumar enjoys playing golf and celebrating the unearned gifts of Holes-in-One, twice. He was part of the winning pair at the DLF Republic Day Cup, also twice. He also won the ‘closest to pin’ contest. In the time left over after golf and professional work, in that order, he writes. This is his fifth book. His Book "उच्छृंखल (Uchhrinkhal)" won the Gold Award for Best Coffee Table Book in Hindi Language by Federation of Indian Publishers.
This book describes recent developments in PV technologies, the solar radiation available on the earth, various BIPVT systems and their applications, energy and exergy analysis, carbondioxide migration and credit earned, life cycle cost analysis and life cycle conversion efficiency.
About Book: Human beings are not wired for predictability of feeling nor for the conduct of selfhood. One can understand erratic response when in difficulty, but they are inconsistent and self-contradictory, even under safest and sanest of the circumstances. When life charges us with its stresses and sorrows, our devotion to righteousness and justice gets short-circuited with an alarming ease. And yet, paradoxically it is in the laboratory of loss and uncertainty that we calibrate and supercharge our virtues. The protagonist in the stories in this book poignantly float into the whirlpool of life, churning the conscience, extracting the essence of being human and humane. Though, far from being a reformer, Basant Kumar extols, a simple yet powerful deity in the Goddess of Justice that can bring some peace to individuals and collectively, to the society. In the lap of the Goddess of Justice, the self gets detached from the self and transcends into a devotee of the goddess who gives fortitude to bear the pains and tribulations that often result from being just. Goddess of Justice requires no temples and no prayer, no mass movement or numbers to impose its superiority over other deities. This is to be practiced internally without any rituals prescribed by any external entity. It is strictly a matter within the self, by the self, and for the self. About the Author: Basant Kumar holds a degree in Science from the University of Allahabad. He graduated in Civil Engineering with Honours from the University of Roorkee (now IIT Roorkee). He was awarded the University Silver Medal. He retired as the Additional Secretary, Government of India. Very active post-retirement, as an independent freelance consultant in the field of Civil Engineering, he is also an Arbitrator and an Arbitration Consultant. He experienced various facets of life in several fields of activities and multifarious pursuits, as an engineer, administrator, and manager in the corporate world and also on the sports field. This vast exposure left a deep and indelible imprint of the human conduct in different situations on him. He intimately observed the compulsions, fears, and ambitions that navigated people on the path that they traversed in life. The stories in this collection bring out the subtleties of choices that protagonists make driven by their inner fragilities and fortitude. Basant Kumar enjoys playing golf and celebrating the unearned gifts of Holes-in-One, twice. He was part of the winning pair at the DLF Republic Day Cup, also twice. He also won the ‘closest to pin’ contest. In the time left over after golf and professional work, in that order, he writes. This is his second book.
This book explores media planning, media buying and the advertising landscape in India. It provides a comprehensive look into the essential aspects of media strategies for brands and businesses to effectively reach their intended audiences and consumers. The book cuts through and demystifies complex media jargon and theories to provide an understanding of the key concepts for developing a media mix that will yield results for businesses. It discusses media research and theories and offers marketers suggestions on how to use both traditional and digital media effectively to build brands. The first section of the book introduces the basics of media theory, including data collection methodologies and their application. The second section covers the fundamentals of planning a media strategy and advertising plans and campaigns based on the goals of the company or brand. The third section discusses the practical nuances of planning – like media mix selections, media vehicle selections and media buying across all types of media. This book will be of interest to students and researchers of business and management studies, media and communication studies as well as to marketing and media professionals working in different sectors of business.
Revision Notes in Psychiatry, Third Edition continues to provide a clear and contemporary summary of clinical psychiatry and the scientific fundamentals of the discipline. It is an essential study aid for all those preparing for postgraduate examinations in psychiatry and a superb reference for practising psychiatrists.Structured to follow the enti
Highly Commended, BMA Medical Book Awards 2013Previously published as Textbook of Clinical Neuropsychiatry, this book has been re-titled and thoroughly updated, redesigned, and enhanced to include the fundamentals of neuroscience. This highly acclaimed text provides a definitive, clinically oriented, yet comprehensive book covering neuropsychiatry
Learn to implement complex data structures and algorithms using Python Key FeaturesUnderstand the analysis and design of fundamental Python data structuresExplore advanced Python concepts such as Big O notation and dynamic programmingLearn functional and reactive implementations of traditional data structuresBook Description Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications. This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms. What you will learnUnderstand object representation, attribute binding, and data encapsulationGain a solid understanding of Python data structures using algorithmsStudy algorithms using examples with pictorial representationLearn complex algorithms through easy explanation, implementing PythonBuild sophisticated and efficient data applications in PythonUnderstand common programming algorithms used in Python data scienceWrite efficient and robust code in Python 3.7Who this book is for This book is for developers who want to learn data structures and algorithms in Python to write complex and flexible programs. Basic Python programming knowledge is expected.
Understand how implementing different data structures and algorithms intelligently can make your Python code and applications more maintainable and efficient Key Features • Explore functional and reactive implementations of traditional and advanced data structures • Apply a diverse range of algorithms in your Python code • Implement the skills you have learned to maximize the performance of your applications Book Description Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You'll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer. By the end of this Python book, you'll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications. What you will learn • Understand common data structures and algorithms using examples, diagrams, and exercises • Explore how more complex structures, such as priority queues and heaps, can benefit your code • Implement searching, sorting, and selection algorithms on number and string sequences • Become confident with key string-matching algorithms • Understand algorithmic paradigms and apply dynamic programming techniques • Use asymptotic notation to analyze algorithm performance with regard to time and space complexities • Write powerful, robust code using the latest features of Python Who this book is for This book is for developers and programmers who are interested in learning about data structures and algorithms in Python to write complex, flexible programs. Basic Python programming knowledge is expected.
The objective of this monograph is to improve the performance of the sentiment analysis model by incorporating the semantic, syntactic and common-sense knowledge. This book proposes a novel semantic concept extraction approach that uses dependency relations between words to extract the features from the text. Proposed approach combines the semantic and common-sense knowledge for the better understanding of the text. In addition, the book aims to extract prominent features from the unstructured text by eliminating the noisy, irrelevant and redundant features. Readers will also discover a proposed method for efficient dimensionality reduction to alleviate the data sparseness problem being faced by machine learning model. Authors pay attention to the four main findings of the book : -Performance of the sentiment analysis can be improved by reducing the redundancy among the features. Experimental results show that minimum Redundancy Maximum Relevance (mRMR) feature selection technique improves the performance of the sentiment analysis by eliminating the redundant features. - Boolean Multinomial Naive Bayes (BMNB) machine learning algorithm with mRMR feature selection technique performs better than Support Vector Machine (SVM) classifier for sentiment analysis. - The problem of data sparseness is alleviated by semantic clustering of features, which in turn improves the performance of the sentiment analysis. - Semantic relations among the words in the text have useful cues for sentiment analysis. Common-sense knowledge in form of ConceptNet ontology acquires knowledge, which provides a better understanding of the text that improves the performance of the sentiment analysis.
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